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  1. Transforming machine learning heuristics into provable algorithms: classical, stochastic, and neural

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  2. Optimal Subset Selection for Causal Inference Using Machine Learning and Particle Swarm Optimization

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  3. Application of Engineering Principles with a Comparison of Machine Learning Classification Methods to Predict Treatment Outcomes in Head and Neck Cancer Patients

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  4. The ALISA Component Module: General Shape Classification for Digital Radiographic Images

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  5. Robust Classification of Emotion in Human Speech Using Spectrogram Features

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